[PDF] Top 20 NULI at SemEval 2019 Task 6: Transfer Learning for Offensive Language Detection using Bidirectional Transformers

... shared task include: a) comparatively small dataset makes it hard to train complex models; b) the characteristics of language on social media pose difficulties such as out-of- vocabulary words and ... See full document

... to SemEval-2019 for three Sub-tasks of Task 6: Sub-task A, Sub-task B, and Sub-task ...categorise offensive lan- ...2-layer bidirectional long short-term ... See full document

... in language modeling by learning context-sensitive representations of ...by learning representations that are functions of the entire input sentence (Peters et ...two bidirectional LSTM ... See full document

... speech detection as an additional source of knowledge and to address the problem of overfit- ting in our deep learning ...filtered using a lexicon of common hate speech ...speech, offensive ... See full document

... comments using neural language models for hate speech ...deep learning using CNN models to detect the hate speech as “racism”, “sexism”, “both” and “non- ... See full document

... of offensive language is an ubiquitous problem one faces when using social networking services like ...for using the computer-mediated communication to engage in offensive behaviour ... See full document

... and Language Processing lab at DA-IICT, In- dia in Semeval-19 OffenEval ...shared task is to identify offensive con- tent at fined-grained level ...The task is divided into three ...any ... See full document

... deep learning model. For clas- sification model, bidirectional long-short memory neural network can catch the contextual informa- tion in text, in order to get offensive semantics from ...the ... See full document

... two SemEval- 2019 competition tasks: Task 5 hatEval “Multilin- gual detection of hate speech against immigrants and women in Twitter” Basile et ...and Task 6 OffensEval “Identi- ... See full document

... and offensive lan- guage detection has mostly focused on supervised machine learning techniques (Mathur et ...shared task on identifying aggression in social media (Kumar et ...shared ... See full document

... Natural Language Process- ing (NLP) latest model, Bidirectional Encoder Representations from Transformers ...that using the original data will give the best ...up using the original ... See full document

... toxicity detection and evaluates their performance in identify- ing and categorizing offensive language in so- cial ...machine learning models for the im- provement of conversations online, as ... See full document

... by using a gating ...a bidirectional GRU, where the con- catenated feature maps, which resulted from the convolutional layer, are used as input for the GRU ... See full document

... Model architecture: We employ a neural net- work architecture implemented with the Keras framework for Python 1 as shown in Fig. 1. It com- bines a bi-directional Gated Recurrent Unit (GRU) layer (Cho et al., 2014) with ... See full document

... Speech Detection dataset and experiments with different machine learning models, such as logistic regression, na¨ıve Bayes, random forests, and lin- ear SVMs to investigate hate speech and offensive ... See full document

... fensive language has seen an upsurge in so- cial ...such offensive posts and take necessary action to monitor and control their ...by using sophisticated deep learning techniques like LSTM, ... See full document

... In the sub-task of detecting the target of offensive language, the information of the part-of-speech tagging process of the tweets is used. This allows us to make more fine-grained distinctions on ... See full document

... Most of these works, however, either assume relatively balanced data (traditional classifiers) and/or large amounts of labeled data (deep learn- ing). In scenarios where only highly imbalanced data are available, it ... See full document

... Offensive language detection is an active re- search area, and several research efforts aim to contribute datasets, propose taxonomies, and im- prove current models to identify offensive con- ... See full document

... This paper examines different approaches and models towards offensive tweet classification which were used as a part of the OffensE- val 2019 competition. It reviews Tweet pre- processing, techniques for ... See full document